航空发动机限寿件疲劳可靠度计算新方法

doi:10.7527/S1000-6893.2019.23228

Abstract

Abstract: Aiming at the small failure probability events and the strong non-linearity of limit state function in the fatigue reliability analysis of aero-engine Limited Life Parts (ELLP), a fatigue reliability analysis method based on the Auto Updating Monte Carlo Radius-Outside Adaptive Importance Sampling (AUMCROAIS) is proposed. In this method, the Monte Carlo Adaptive Importance Sampling (MCAIS) is used to approach the Most Probable Point (MPP) efficiently, then the polar coordinate sampling is employed by taking the approximate MPP as the sampling center. An active learning function is constructed to optimize the near-limit state function and sampling radius, so that the optimal sampling radius can be updated. The optimal sampling radius can be determined through continuous updating, accelerating the convergence of failure probability. This method improves the convergence speed of MPP points and ensures the accuracy of calculation. It solves the problem of reliability calculation of small failure probability events and strong non-linear limit state function. Finally, taking a compressor disk of an engine as an application, and the efficiency, robustness and simulation accuracy of the proposed method are verified by comparing with the traditional Monte Carlo Simulation (MCS) method, the Monte Carlo Radius-Outside Adaptive Importance Sampling (MCROAIS), and First-Order Reliability Method (FORM).

Key words: fatigue reliability, aero-engine, adaptive importance sampling, automatic updating, active learning

CLC Number:

YOU Lingfei, ZHANG Jianguo, ZHOU Shuang, DU Xiaosong. A new method for fatigue reliability calculation of aero-engine limited life parts[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2019, 40(12): 223228-223228.

References 26

[1]	U.S. Department of Transportation, Federal Aviation Administration. Guidance material for aircraft engine life limit parts requirement:Advisory Circular 33.70-1[R]. Washington, D.C.:FAA, 2009:30-50.
[2]	VITTALS S, HAJELA P, JOSHI A. Review of approaches to gas turbine life management:AIAA-2004-4372[R]. Reston,VA:AIAA, 2004.
[3]	BEACHKOFSKI B K, GRANDHI R V. Probabilistic system reliability for a turbine engine airfoil[C]//ASME Turbo Expo 2004:Power for Land, Sea, and Air. New York:ASME, 2004:171-179.
[4]	MELIS M E, ZARETSKY E V,AUGUST R. Probabilistic analysis of aircraft gas turbine disk life and reliability[J]. Journal of Propulsion and Power, 1999, 15(5):658-666.
[5]	GAO H, FEI C, BAI G. Reliability-based low-cycle fatigue damage analysis for turbine blade with thermo-structural interaction[J].Aerospace Science & Technology, 2016, 49:289-300.
[6]	ZHU S P, LIU Q, PENG W, et al. Computational-experimental approaches for fatigue reliability assessment of turbine bladed disks[J]. International Journal of Mechanical Sciences, 2018,142:502-517.
[7]	ZHU S P, LIU Q, ZHOU J. Fatigue reliability assessment of turbine discs under multi-source uncertainties[J]. Fatigue & Fracture of Engineering Materials & Structures, 2018,4:1291-1305.
[8]	HU D Y, MA Q H, SHANG L H,et al. Creep-fatigue behavior of turbine disc of superalloy GH720Li at 650℃ and probabilistic creep-fatigue modeling[J]. Materials Science & Engineering A, 2016,670:17-25.
[9]	WANG R Q, LIU X, HU D Y, et al.Zone-based reliability analysis on fatigue life of GH720Li turbine disk concerning uncertainty quantification[J]. Aerospace Science and Technology, 2017,70:300-309.
[10]	李岩, 张曙光, 宫綦. 一种改进的航空发动机结构概率风险评估方法[J]. 航空学报, 2016, 37(2):597-608. LI Y,ZHANG S G,GONG Q. An improved probabilistic risk assessment method of structural parts for aeroengine[J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(2):597-608(in Chinese).
[11]	陈志英, 谷裕, 周平, 等. 基于应力应变场强法的轮盘疲劳可靠性分析方法[J]. 推进技术, 2018,39(2):433-439. CHEN Z Y,GU Y,ZHOU P,et al. Fatigue reliability analysis of disk based on stress-strain field intensity method[J]. Journal of Propulsion Technology, 2018,39(2):433-439(in Chinese).
[12]	刘君强, 谢吉伟,左洪福,等.基于随机Wiener过程的航空发动机剩余寿命预测[J].航空学报,2015,36(2):564-574. LIU J Q, XIE J W, ZUO H F, et al. Residual lifetime prediction for aeroengines based on Wiener process with random effects[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(2):564-574(in Chinese).
[13]	姚伟,白广忱.基于Fourier正交基神经网络的涡轮盘低循环疲劳可靠性分析[J]. 装备制造技术,2014,(10):132-134. YAO W,BAI G C. Reliability analysis of low cycle fatigue of turbine disk based on fourier orthogonal neural network[J]. Equipment Manufacturing Technology,2014,(10):132-134(in Chinese).
[14]	皮骏, 马圣, 贺嘉诚, 等. 遗传算法优化的SVM在航空发动机磨损故障诊断中的应用[J]. 润滑与密封, 2018, 43(10):95-103. PI J, MA S, HE J C,et al. Application of genetic algorithm optimized SVM in aeroengine wear fault diagnosis[J]. Lubrication Engineering, 2018, 43(10):95-103(in Chinese).
[15]	TOMASSON E, SODER L. Improved importance sampling for reliability evaluation of composite power systems[J]. IEEE Transactions on Power Systems, 2017,32(3):2426-2434.
[16]	LI L, LU Z Z. Interval optimization based line sampling method for fuzzy and random reliability analysis[J]. Journal of Applied Mathematics, 2014,38(13):3124-3135.
[17]	XIONG B, TAN H F. A robust and efficient structural reliability method combining radial-based importance sampling and Kriging[J]. Science China Technological Sciences, 2018,61(5):724-734.
[18]	MELCHERS R E. Search-based importance sampling[J]. Structural Safety,1990, 9:117-128
[19]	AU S K, BECK J L. A new adaptive importance sampling scheme for reliability calculations[J]. Structural Safety, 1999, 21:135-158.
[20]	SANKARAN M, PRAKASB L. Adaptive simulation for system reliability analysis of large structures[J].Computers and Stmctures,2000,77:725-734.
[21]	黄毅,王明政,颜寒,等. 快堆中心柱低周疲劳可靠性评价[J]. 原子能科学技术,2018,52(1):118-125. HUANG Y, WANG M Z, YAN H, et al. Low cycle fatigue reliability evaluation of central column in fast reactor[J]. Atomic Energy Science and Technology, 2018,52(1):118-125(in Chinese).
[22]	陈向前,董聪,闫阳.自适应重要抽样方法的改进算法[J]. 工程力学,2012,29(11):123-128. CHEN X Q, DONG C, YAN Y. Improved adaptive important sampling algorithm[J]. Engineering Mechanics, 2012,29(11):123-128(in Chinese).
[23]	马纪明,詹晓燕,曾声奎.基于自适应重要抽样的可靠性分析方法[J]. 北京航空航天大学学报,2011,37(9):1142-1150. MA J M, ZHAN X Y, ZENG S K. Reliability analysis method based on adaptive importance sampling[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011,37(9):1142-1150(in Chinese).
[24]	戴鸿哲,赵威,王伟.结构可靠性高效自适应重要抽样方法[J].力学学报,2011,4(6):1133-1140. DAI H Z, ZHAO W, WANG W. An efficient adaptive important sampling method for structural reliability analysis[J].Chinese Journal of Theoretical and Applied Mechanics, 2011,4(6):1133-1140(in Chinese).
[25]	U. S. Department of Transportation, Federal Aviation Administration Airworthiness Standards. Aircraft engines:CFR 14 Part 33[S]. Washington, D.C.:FAA,2009:10-30.
[26]	吴学仁.飞机结构金属材料力学性能手册:静强度疲劳-耐久性[M].北京:航空工业出版社, 1997:30-35. WU X R.Handbook of mechanical prosperities of aircraft structural metals:Static strength/durability[M]. Beijing:Aviation Industry Press, 1997:30-35(in Chinese).

A new method for fatigue reliability calculation of aero-engine limited life parts

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References 26

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Yulian GONG, Jianguo ZHANG, Zhigang WU, Guangyuan CHU, Xiaoduo FAN, Ying HUANG. Reliability algorithm of composite structure based on active learning basis-adaptive PC-Kriging model [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(8): 228982-228982.
[2]	Zeyong YIN, Gaiqi LI, Jiancheng SHI, Yueqian YIN. Concept, method and practice of advanced versatile core engine derivative [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(7): 29713-029713.
[3]	Weina HUANG, Fangjuan LI, Hongbin QI. Preliminary investigation and thoughts on aero-engine digital engineering development [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(5): 529693-529693.
[4]	Ruixian MA, Xin WANG, Kaiming WANG, Bin LI, Mingfu LIAO, Siji WANG. Rubbing experimental study on labyrinth and rubber⁃coated case for aero⁃engines [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(4): 628350-628350.
[5]	Yuan XIAO, Kun FENG, Minghui HU, Zhinong JIANG. Extraction method for unsteady vibration components of aero-engine rotors [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(3): 228158-228158.
[6]	Yingjiao HU, Feng XU, Zhijun YANG. Overview of aero-engine ice testing capability [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(S2): 729449-729449.
[7]	Neng WAN, Qixin ZHUANG, Yanheng GUO, Zhiyong CHANG, Dao WANG. Sampling strategy for on-machine measurement of aero-engine blade under constraint of fitting accuracy [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(7): 427151-427151.
[8]	Feng JIANG, Huacong LI, Jiangfeng FU, Linxiong HONG. A RBF and active learning combined method for structural non-probabilistic reliability analysis [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(2): 226667-226667.
[9]	Miaodong ZHAO, Dianyin HU, Jianxing MAO, Haihe SUN, Shiyong QIN, Yuanxing GU, Rongqiao WANG, Tengyue TIAN, Lin YAN, Zhixing XIAO. Simulating specimen for low cycle fatigue of aero-engine disc: Design and experiment [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(18): 228320-228320.
[10]	Xiaofeng SUN, Guangyu ZHANG, Xiaoyu WANG, Lei LI, Xiangyang DENG, Ronghui CHENG. Research progress in aero-engine combustion instability prediction and control [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(14): 628733-628733.
[11]	Pei PENG, Yongping ZHAO, Yuwei WANG. New method for automatic and rapid mining of aero-engine operating patterns [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(11): 327659-327659.
[12]	Wanli ZHAO, Yingqing GUO, Kejie XU, Cansen WANG, Haojie YING, Xinxin TAO. Review of key technologies for fault diagnosis and accommodation for multi⁃electric distributed engine control system [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(10): 27519-027519.
[13]	ZHANG Zhongqiang, ZHANG Xin, WANG Jiaxu, LIU Zhiwen. Reweighted kurtogram for aero-engine fault diagnosis [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 625445-625445.
[14]	HAN Songyu, SHAO Haidong, JIANG Hongkai, ZHANG Xiaoyang. Intelligent fault diagnosis of aero-engine high-speed bearings using enhanced CNN [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 625479-625479.
[15]	DU Jianjian, PAN Xiande, LIU Tianyi. Indirect measurement method for axial load of aero-engine angular contact ball bearing [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 625457-625457.